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A电力公司客户关系管理系统构建-从大数据角度出发_MBA毕业论文

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“大数据”是近年来学术研究的热点问题,国家十三五计划也把“大数据应 用”列为百项重点工程中。2017 年 1 月,工信部发布了《大数据产业发展规划 2016-2020 年》之后,大数据在零售、医疗、电信、金融、制造等行业的实际应 用更是开始了大踏步的前进。关于大数据的研究也从理论和技术的探讨向其在商 业中的应用延伸。企业价值的实现来自于客户,而客户关系管理探讨的是企业如 何通过为客户提供优质的产品和服务,实现客户满意,通过与客户建立良好的关 系,深度挖掘客户能为企业带来的价值。基于此,本文将探讨大数据在企业客户 关系管理中的应用。 本文以 A 电力公司作为研究对象,首先探讨了与客户关系管理和大数据相关 的基本概念,以及大数据在客户关系管理中的应用;其次分析了 A 电力公司客户 关系管理的现状;再次,分析了 A 电力公司大数据平台的构建;然后,在此基础 上详细分析了 A 电力公司基于大数据的客户关系管理系统构建。 通过分析发现,大数据为客户关系管理系统的构建提供了强有力的决策参 考,而客户关系管理系统的应用可以有效提高企业运营效率,降低运营成本,优 化服务质量,改善企客关系。同时大数据分析也帮助企客关系的维护和系统优化 之间形成互相促进的良性发展。 本文的研究不仅可以扩充客户关系管理在传统行业的理论外延,为电力行业 客户关系管理能力和质量的提升提供相应的意见和建议,进而为传统行业利用大 数据进行客户关系管理提供参考价值。 关键词:大数据;客户关系;客户价值II ABSTRACT Big data has been a hot topic in academic research in recent years, and big data application has been listed as one of the 100 key projects in the 13th five-year plan. In January 2017, after the ministry of industry and information technology released the 2016-2020 development plan for big data industry, the practical application of big data in retail, medical, telecommunications, finance, manufacturing and other industries started to make great strides. The research on big data also extends from the discussion of theory and technology to its application in business. The realization of enterprise value comes from customers, while customer relationship management discusses how enterprises can achieve customer satisfaction by providing customers with high-quality products and services. Based on customer satisfaction, enterprises can establish good relations with customers, and then deeply explore the value customers can bring to enterprises. Therefore, This paper will discuss the application of big data in enterprise customer relationship management. Taking electricity company A as the research object, this paper first discusses the basic concepts related to CRM and big data, and the application of big data in CRM. Secondly, the status quo of customer relationship management of electricity company A is analyzed. Thirdly, this paper talks about the construction of electricity company A's big data platform. Then, detailed analysis is about the construction of electricity company A's customer relationship management system based on big data. It is found that big data provides a powerful decision-making reference for the construction of CRM system, and the application of CRM system can effectively improve the operation efficiency of enterprises, reduce the operation cost, optimize the service quality and improve the relationship between enterprises and customers. Meanwhile, big data analysis also helps maintain the relationship between enterprises and customers and optimize the system to form a mutually promoting benign development. The research in this paper can not only expand the theoretical extension of CRM in traditional industries, but also provide corresponding opinions and suggestions for the improvement of customer relationship management in power industry, so as to provide reference value for the use of big data in customer relationship management in traditional industries. Keywords: Big data; Customer relationships; Customer valueIII 目录 第一章 绪论 ............................................................... 1 1.1 研究的背景和意义................................................... 1 1.1.1 研究背景..................................................... 1 1.1.2 研究意义 .................................................... 2 1.2 研究内容 .......................................................... 2 1.3 研究方法 .......................................................... 3 1.4 研究思路框架 ...................................................... 3 第二章 客户关系管理与大数据 ............................................... 5 2.1 客户关系管理相关理论 .............................................. 5 2.1.1 客户关系管理概念 ............................................ 5 2.1.2 客户关系管理的理论基础 ...................................... 6 2.1.3 客户关系管理的核心思想 ...................................... 8 2.1.4 客户关系管理流程 ........................................... 10 2.2 国内外客户关系管理研究现状 ....................................... 11 2.2.1 国外客户关系管理研究现状.................................... 11 2.2.2 国内客户关系管理研究现状.................................... 12 2.3. 大数据的相关概念 ................................................ 14 2.3.1 大数据的定义................................................ 14 2.3.2 大数据的特征................................................ 14 2.4 大数据技术与客户关系管理 ......................................... 15 第三章 A 电力公司客户关系管理现状 ......................................... 17 3.1 公司客户关系管理背景 ............................................. 17 3.2 客户关系管理服务情况 ............................................. 17 3.3 A 电力公司客户关系管理存在问题.................................... 19 3.4 推广应用及效益分析 ............................................... 20 第四章 A 电力公司大数据分析平台构建....................................... 22 4.1 大数据平台的构建 ................................................. 22 4.2 大数据分析应具备的条件 ........................................... 23 4.2.1 平台运行模块................................................ 23 4.2.2 平台管理模块................................................ 24 4.3 大数据分析 ....................................................... 26 4.3.1 系统功能.................................................... 26 4.3.2 用户行为分析指标............................................ 27 第五章 基于大数据的客户关系管理系统构建 .................................. 30IV 5.1 项目总体结构...................................................... 30 5.2 内网建设与外网建设................................................ 31 5.2.1 内网建设.................................................... 31 5.2.2 外网建设.................................................... 31 5.3 移动应用建设 ..................................................... 34 5.4 末端综合支撑 ..................................................... 36 5.5 A 电力公司客户关系管理系统的作用.................................. 38 第六章 总结 .............................................................. 40 6.1 大数据在客户关系管理应用中的策略建议 ............................. 40 6.1.1 面向内部员工................................................ 40 6.1.2 面向外部客户................................................ 41 6.2 结论 ............................................................. 42 6.3 本文的研究不足.................................................... 43 6.4 研究展望 ......................................................... 43